A Tsetlin machine is an artificial intelligence algorithm based on propositional logic.
Background A Tsetlin machine is a form of learning automaton collective for learning patterns using propositional logic. Ole-Christoffer Granmo created and gave the method its name after Michael Lvovitch Tsetlin, who invented the Tsetlin automaton and worked on Tsetlin automata collectives and games. Collectives of Tsetlin automata were originally constructed, implemented, and studied theoretically by Vadim Stefanuk in 1962. The Tsetlin machine uses computationally simpler and more efficient primitives compared to more ordinary artificial neural networks. As of April 2018 it has shown promising results on a number of test sets.
Types Original Tsetlin machine Convolutional Tsetlin machine Regression Tsetlin machine Relational Tsetlin machine Weighted Tsetlin machine Arbitrarily deterministic Tsetlin machine Parallel asynchronous Tsetlin machine Coalesced multi-output Tsetlin machine Tsetlin machine for contextual bandit problems Tsetlin machine autoencoder Tsetlin machine composites: plug-and-play collaboration between specialized Tsetlin machines Contracting Tsetlin machine with absorbing automata Graph Tsetlin machine Fuzzy-Pattern Tsetlin Machine
Applications Keyword spotting Aspect-based sentiment analysis Word-sense disambiguation Novelty detection Intrusion detection Semantic relation analysis Image analysis Text categorization Fake news detection Game playing Batteryless sensing Recommendation systems Word embedding ECG analysis Edge computing Bayesian network learning Federated learning Text generation
Original Tsetlin machine
Tsetlin automaton The Tsetlin automaton is the fundamental learning unit of the Tsetlin machine. It tackles the multi-armed bandit problem, learning the optimal action in an environment from penalties and rewards. Computationally, it can be seen as a finite-state machine (FSM) that changes its states based on the inputs. The FSM will generate its outputs based on the current states. A quintuple describes a two-action Tsetlin automaton:
{ Φ _ , α _ , β _ , F ( ⋅ , ⋅ ) , G ( ⋅ ) } . {\displaystyle \{{\underline {\Phi }},{\underline {\alpha }},{\underline {\beta }},F(\cdot ,\cdot ),G(\cdot )\}.}
A Tsetlin automaton has 2 n {\displaystyle 2n} states, here 6:
Φ _ = { ϕ 1 , ϕ 2 , ϕ 3 , ϕ 4 , ϕ 5 , ϕ 6 } {\displaystyle {\underline {\Phi }}=\{\phi _{1},\phi _{2},\phi _{3},\phi _{4},\phi _{5},\phi _{6}\}}
The FSM can be triggered by two input events
β _ = { β P e n a l t y , β R e w a r d } {\displaystyle {\underline {\beta }}=\{\beta _{\mathrm {Penalty} },\beta _{\mathrm {Reward} }\}}
The rules of state migration of the FSM are stated as
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